We’re looking for a hands-on Data Scientist to join as the first hire in our data science function, reporting directly to the Back-End Manager. This is a high-impact role where you’ll own the full lifecycle of projects - from concept through deployment - and set the technical and analytical foundations for future growth. You’ll develop advanced predictive models for sports forecasting and ad-tech optimization, directly influencing product decisions and revenue outcomes.

About Sidelines

Sidelines Group is one of the fastest-growing sports betting and iGaming affiliate companies in the industry, specializing in experience-driven technology. We’re looking for employees who are ambitious, willingly take ownership, and execute effectively — all to power the company forward

What will you do?

• Full Ownership of Data Science Projects - Lead initiatives end-to-end: problem definition, data gathering, model development, deployment, monitoring, and iteration.
• Sports Forecasting Models - Design and train statistical and machine learning models for predicting sports outcomes, player performance, and betting-related probabilities.
• Ad-Tech Optimization - Build predictive and prescriptive models to improve user targeting, click-through rates, conversion probabilities, and ad inventory value.
• Innovation & Research - Explore emerging ML/AI techniques in sports analytics, recommendation systems, and bidding optimization; translate findings into actionable solutions.
• Visualization & Communication - Present results through intuitive dashboards, visualizations, and clear storytelling to both technical and non-technical stakeholders.
• Cross-Team Collaboration - Partner with engineering, product, and business teams to identify opportunities, prioritize efforts, and deliver measurable impact.
  
  
  

What will you bring to the table?

• BSc in Data Science (preferred) or in Computer Science/Software Engineering with a strong academic foundation in machine learning - Mandatory.
• 3+ years of experience in a Data Science role
• Strong statistical and mathematical foundations (probability theory, regression, linear algebra, time-series analysis).
• Proven expertise in Python with data science/ML libraries (Pandas, NumPy, Scikit-learn, LightGBM, XGBoost, TensorFlow/PyTorch) and OOP principles.
• Experience writing and optimizing SQL queries.
• Demonstrated ability to take models from notebook to production.
• Experience with BigQuery - advantage.
• Background in sports analytics or ad-tech - strong advantage.
• Master’s degree with thesis in a quantitative discipline - advantage.